representing uncertainty in situation maps for disaster management
TRANSCRIPT
REPRESENTING UNCERTAINTY IN SITUATION MAPS FOR
DISASTER MANAGEMENT J. Hild, S. Eckel, J. Geisler
Fraunhofer IITB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany
Abstract Emergency staff perform their task under mental and time pressure, especially when leading the emergency
operation on-scene next to the damaged area. The mobile command vehicle provides lots of supporting tools to
conduct the operation successfully. We here focus on the situation map. It is used by the emergency staff to
provide an overview of all operational information at a glance. The map contains certain and uncertain
information, which is to be displayed differently. In this work we analyse the state-of-the-art uncertainty
representation both from a theoretical and practical point of view, and examine alternative uncertainty
representation techniques. We propose two new techniques to display uncertain information. In an empirical
evaluation we show that these techniques allow a higher performance of the map-reader than the state-of-the-art
technique in terms of classifying the displayed information correctly. Given that there is reduced space for the
situation map in a mobile command vehicle compared to stationary emergency operation centers, space-saving
uncertainty representation proposals could be particularly interesting for displaying situation maps on smaller
screens.
1. Application domain and requirements The situation map is an important tool to support emergency staff. It plays a key role during the
emergency management process as the sole source for an overview of the emergency situation at a
glance. For this purpose, the relevant operational information is depicted on the map using a specific
symbol set which represents damages and dangers. In this context, it is necessary to distinguish
between certain and uncertain (e. g. incomplete or probably incorrect) information, because uncertain
information critically affects human resources planning. The German emergency operations manual
refers to this requirement by specifying a particular representation of uncertain information in situation
maps [1]. In this state-of-the-art representation uncertain information is marked by preceding the
coding symbol by a question mark “?”. Figure 1 shows an exemplary situation map. It has been
verified by a professional fire-fighter, experienced in conducting operations in mobile command
vehicles.
Figure 1: Exemplary Situation Map
Especially when leading the emergency operation on-scene next to the damaged area, emergency
managers perform their tasks under high mental and time-pressure. It is therefore particularly
important for them to focus on their major task of conducting the disaster operation. In consequence,
any ancillary task should be easy to carry out, i. e. with minimal cognitive load, especially for the
short-term memory. With respect to the usage of the situation map, this can be achieved by a plain and
clear visualization of the relevant operational information as well as an easy interpretable
discrimination of certain versus uncertain information.
In this work we examine representations of uncertain information in situation maps. The aim of our
investigation is to minimize the cognitive load of the human map-reader by finding an optimized
representation for uncertain information. Additionally, a space-saving representation could be
particularly useful for displaying situation maps on smaller screens, as found in narrow mobile
command vehicles.
2. State of the art The basis of our work is the state-of-the-art representation of situation reports by situation maps. The
base map for our situation is a commonly used topographic map. We have chosen this type of map
because of its detailed graphics, due to which it is difficult to easily detect tactical symbols at arbitrary
locations on the map. A representation which works on this type of map would also work on every less
detailed map. Furthermore, topographical maps are available both as analogous and as digital maps.
Although situation maps are still often paper maps, we decided to to follow our fire-fighter, who
pointed out lots of advantages of using digital situation maps; especially when supporting emergency
operations in far-off areas, loading the corresponding map from the internet allows to start with
preparing the situation map already on the way to the damaged area. As symbol set we use the German
tactical symbols as specified by the German emergency operations manual [1].
As a basis for finding appropriate uncertainty representation techniques we present a hierarchical
overview of the status quo of the research in this domain, focussed on contributions by the cartography
and scientific visualization community [2, 3]. As a result we get the tree-structure depicted in Figure 2:
In the leaf nodes currently used representation techniques are listed, while the inner nodes describe
their representational properties.
Figure 2: Taxonomy of Uncertainty Representation Techniques [4]
As assessment criterion to decide on the suitability of a representation technique we use findings from
the human engineering area. We consider the aspect of a representations’ conspicuousness as well as
the aspect of the limitation of human perception as described by the Model Human Processor [5],
especially focussing on the bottleneck nature of the short-term memory for the human cognition as a
whole. Concerning this matter, a key requirement is to find an uncertainty representation which
occupies as few chunks as possible in the short-term memory.
3. Theoretical results In our work uncertainty is displayed as binary information – i.e., the operational information is
assumed to be certain or uncertain, without any intermediate levels in between. It has been shown that
the mapping between human statements about uncertainty and numerical measures for uncertainty,
such as probability, is difficult [6]. Considering multiple assessments of a dangerous situation, – for
example first by the investigating fire-fighter, second by the staff member in the mobile command
vehicle, who decides on the symbolic representation of the report in the situation map – the ambiguity
in the interpretation of the uncertainty degrees could lead to manifold misinterpretation. This is not
acceptable in a high-stress emergency situation.
3.1 State-of-the-art technique („?“-technique) The state-of-the-art technique introduced above, subsequently called „?“-technique, displays
uncertainty as binary information. Certain information is depicted by a corresponding symbol, while
uncertain information is displayed by the symbol preceded by a “?” mark. Looking at the tree in
Figure 2, the „?“-technique can be classified as direct, static, bivariate, extrinsic. The “?” is one
possibility to add a geometric object in the broader sense. One advantage of the „?“-technique is the
intuitive, deep-seated meaning of the question mark “?”. In addition it is easily manageable as only
one additional symbol is needed to depict uncertainty. Changing the display from certain to uncertain
(or vice versa) is very simple by adding/removing the “?”-symbol. The drawbacks are as follows:
Every “?” is represented with the same size, color, value, texture and orientation as the corresponding
tactical symbol, and therefore provides little visual discriminability between uncertain versus certain
information. Furthermore, the usage of an additional symbol to mark uncertainty results in an overall
short-term memory load of two chunks.
3.2 Impractical techniques As explained above, the situation map is supposed to give an overview of the emergency situation as a
whole at a glance. This is not possible for the techniques listed under the terms of indirect, direct
dynamic and direct static separate in the tree hierarchy. Using a threshold for displaying binary
uncertainty results in showing either only the certain or all information. Therefore, identifying the
uncertain information requires comparing both displayed states, which results in an unacceptable
cognitive load. Similarly, the dynamic techniques would show the uncertainty of an information over
some period of time, which also prevents to grasp the situation at any time as a whole at a glance. A
side-by-side representation would show the information in one situation map, the corresponding
uncertainties in another, which is also unacceptable.
The intrinsic techniques provide the advantage of occupying only one chunk in the short-term
memory. Also, showing the corresponding uncertainty of an operational information by modifying in
the tactical symbol itself, there will be less occlusion of the base map. The variables position, color,
orientation and shape are already used in the representation of the symbols and thus not free for
displaying uncertainty. Unfortunately, using value, saturation or blurring is also not suitable in our
application. Manipulating these variables to display uncertainty we found, that the conspicuousness of
the symbol against the background of a topographical map is too weak. As the intensity of a stimulus
is inverse to the processing time of the perceptual processor, the time for decoding the symbol will
increase.
3.3 New proposals Two intrinsic techniques turned out to be appropriate: size and texture/grain. The conceived version of
the variable size displays uncertain information with a thinner line (thin-line-technique, see Table 1,
middle). The version of the variable texture/grain displays uncertain information with a dotted line
(dotted-line-technique, see Table 1, right resp. Figure 3). Advantages for both techniques are primarily
the short-term memory load of only one chunk. The concept of uncertainty is intuitively confirmed,
because the uncertain symbols consist of fewer pixels than the certain ones. As the manipulation of a
symbol in order to show uncertainty does not change its major representational properties (same
shape, color, opacity), the original symbol is still easy identifiable. Difficulties in using the new
techniques exist because of the representational properties of the base map. Thus it could be difficult
to choose an appropriate line thickness because there are already many different thicknesses used in
the base map. In the case of the dotted-line-technique it could be difficult to get sufficient
conspicuousness against a dotted background.
Table 1: Symbol examples showing different shapes for uncertainty
Figure 3: The scenario introduced in Figure 1, now using the dotted-line-technique
4. Experiments To complement our theoretical reasoning we carried out an experimental evaluation. We enlisted
seven persons to act as participants, two of them professional fire-fighters, which are familiar with the
„?“-technique as uncertainty representation technique. Their task was to count the numbers of
uncertain and certain information shown in a situation map. We measured their performance using the
following formula [7]:
Performance = #correctly counted symbols / time
The trial was conducted using the horizontal tabletop display of IITB’s Digital Map Surface, a team
workplace designed (also) to be used by emergency staff [8] in both mobile and stationary emergency
operation centers. The result of the experimental evaluation is shown in Table 2. The order of the “test runs” was
analogous to the order of the columns (“?” – “dotted” – “thin”). One striking result is that the dotted-
line-technique comes out with the best performance results. Notably, even the fire-fighters achieve the
worst results with the „?“-technique. We attribute the outcome of the evaluation to the unequal chunk
load of the techniques.
In our future work, we intend to underpin our results by increasing the data base and by refining the
configuration of the experiment in order to suppress learning effects.
Table 2: Evaluation Results; FF = Fire-Fighters (incident commanders)
Acknowledgements We would like to thank the Landesvermessungsamt Baden-Württemberg for having made available
the topographic map. We are also grateful to the Berufsfeuerwehr Karlsruhe for their generous
support. With their expert knowledge and participation in the evaluation they provided valuable input
to our research.
References [1] Feuerwehr-Dienstvorschrift 100. Führung und Leitung im Einsatz. Kohlhammer, 2003
[2] MacEachren A.; Robinson, A.; Hopper, S.; Gardner, St.; Murray, R.; Gahegan, M.;
Hetzler, E.: Visualizing Geospatial Information Uncertainty: What We Know and What We Need to
Know. In: Cartography and Geographic Information Science 32 (2005), no. 3, pp. 139 -- 161
[3] Griethe, H; Schumann, H.: The Visualization of Uncertain Data: Methods and Problems. In:
Proceedings of SimVis 2006, Magdeburg, Germany, April 2006, pp. 143 – 156
[4] Hild, J.: Berücksichtigung unsicherer Information bei Wahrnehmungsgrenzen für Lagekarten im Falle
von Katastrophen. University of Karlsruhe (TH), master thesis, 2008
[5] Card, S.; Moran, Th.; Newell, A.: The Psychology of Human-Computer Interaction, Lawrence Erlbaum
Associates, 1983.
[6] Jungermann, H.; Pfister, H.-R.; Fischer, K.: Die Psychologie der Entscheidung, 2. ed., Elsevier, 2005
[7] Syrbe, M.; Beyerer, J.: Mensch-Maschine-Wechselwirkungen, Anthropotechnik. In: Hütte – das
Ingenieurwissen, 33. ed., Springer, 2007, pp. K80 – K104
[8] Bader, Th.; Meissner, A.; Tscherney, R: Digital Map Table with Fovea Tablet: Smart Furniture for
Emergency Operation Centers. In: Proceedings of the 5th
International ISCRAM Conference,
Washington, DC, USA, 2008